A convective-scale 1,000-member ensemble simulation and potential applications

Autores
Necker, Tobias; Geiss, Stefan; Weissmann, Martin; Ruiz, Juan Jose; Miyoshi, Takemasa; Lien, Guo Yuan
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This study presents the first convective-scale 1,000-member ensemble simulation over central Europe, which provides a unique data set for various applications. A comparison with the operational regional 40-member ensemble of Deutscher Wetterdienst shows that the 1,000-member simulation exhibits realistic spread properties overall. Based on this, we discuss two potential applications. First, we quantify the sampling error of spatial covariances of smaller subsets compared with the 1,000-member simulation. Knowledge about sampling errors and their dependence on ensemble size is crucial for ensemble and hybrid data assimilation and for developing better approaches for localization in this context. Secondly, we present an approach for estimating the relative potential impact of different observable quantities using ensemble sensitivity analysis. This will provide the basis for consecutive studies developing future observation and data assimilation strategies. Sensitivity studies on the ensemble size indicate that about 200 ensemble members are required to estimate the potential impact of observable quantities with respect to precipitation forecasts.
Fil: Necker, Tobias. Ludwig Maximilians Universitat; Alemania. Universidad de Viena; Austria
Fil: Geiss, Stefan. Ludwig Maximilians Universitat; Alemania
Fil: Weissmann, Martin. Ludwig Maximilians Universitat; Alemania
Fil: Ruiz, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Fil: Miyoshi, Takemasa. RIKEN Center for Computational Science; Japón
Fil: Lien, Guo Yuan. RIKEN Center for Computational Science; Japón
Materia
CONVECTIVE-SCALE
COVARIANCE
DATA ASSIMILATION
ENSEMBLE SENSITIVITY ANALYSIS
LOCALIZATION
OBSERVING SYSTEM
SAMPLING ERROR
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/143882
Acceder
id CONICETDig_2fb73ea4da496ff42e18e437406faec5
oai_identifier_str oai:ri.conicet.gov.ar:11336/143882
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A convective-scale 1,000-member ensemble simulation and potential applicationsNecker, TobiasGeiss, StefanWeissmann, MartinRuiz, Juan JoseMiyoshi, TakemasaLien, Guo YuanCONVECTIVE-SCALECOVARIANCEDATA ASSIMILATIONENSEMBLE SENSITIVITY ANALYSISLOCALIZATIONOBSERVING SYSTEMSAMPLING ERRORhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1This study presents the first convective-scale 1,000-member ensemble simulation over central Europe, which provides a unique data set for various applications. A comparison with the operational regional 40-member ensemble of Deutscher Wetterdienst shows that the 1,000-member simulation exhibits realistic spread properties overall. Based on this, we discuss two potential applications. First, we quantify the sampling error of spatial covariances of smaller subsets compared with the 1,000-member simulation. Knowledge about sampling errors and their dependence on ensemble size is crucial for ensemble and hybrid data assimilation and for developing better approaches for localization in this context. Secondly, we present an approach for estimating the relative potential impact of different observable quantities using ensemble sensitivity analysis. This will provide the basis for consecutive studies developing future observation and data assimilation strategies. Sensitivity studies on the ensemble size indicate that about 200 ensemble members are required to estimate the potential impact of observable quantities with respect to precipitation forecasts.Fil: Necker, Tobias. Ludwig Maximilians Universitat; Alemania. Universidad de Viena; AustriaFil: Geiss, Stefan. Ludwig Maximilians Universitat; AlemaniaFil: Weissmann, Martin. Ludwig Maximilians Universitat; AlemaniaFil: Ruiz, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Miyoshi, Takemasa. RIKEN Center for Computational Science; JapónFil: Lien, Guo Yuan. RIKEN Center for Computational Science; JapónJohn Wiley & Sons Ltd2020-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/143882Necker, Tobias; Geiss, Stefan; Weissmann, Martin; Ruiz, Juan Jose; Miyoshi, Takemasa; et al.; A convective-scale 1,000-member ensemble simulation and potential applications; John Wiley & Sons Ltd; Quarterly Journal of the Royal Meteorological Society; 146; 728; 4-2020; 1423-14420035-9009CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/qj.3744info:eu-repo/semantics/altIdentifier/doi/10.1002/qj.3744info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:05:12Zoai:ri.conicet.gov.ar:11336/143882instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:05:13.232CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A convective-scale 1,000-member ensemble simulation and potential applications
title A convective-scale 1,000-member ensemble simulation and potential applications
spellingShingle A convective-scale 1,000-member ensemble simulation and potential applications
Necker, Tobias
CONVECTIVE-SCALE
COVARIANCE
DATA ASSIMILATION
ENSEMBLE SENSITIVITY ANALYSIS
LOCALIZATION
OBSERVING SYSTEM
SAMPLING ERROR
title_short A convective-scale 1,000-member ensemble simulation and potential applications
title_full A convective-scale 1,000-member ensemble simulation and potential applications
title_fullStr A convective-scale 1,000-member ensemble simulation and potential applications
title_full_unstemmed A convective-scale 1,000-member ensemble simulation and potential applications
title_sort A convective-scale 1,000-member ensemble simulation and potential applications
dc.creator.none.fl_str_mv Necker, Tobias
Geiss, Stefan
Weissmann, Martin
Ruiz, Juan Jose
Miyoshi, Takemasa
Lien, Guo Yuan
author Necker, Tobias
author_facet Necker, Tobias
Geiss, Stefan
Weissmann, Martin
Ruiz, Juan Jose
Miyoshi, Takemasa
Lien, Guo Yuan
author_role author
author2 Geiss, Stefan
Weissmann, Martin
Ruiz, Juan Jose
Miyoshi, Takemasa
Lien, Guo Yuan
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv CONVECTIVE-SCALE
COVARIANCE
DATA ASSIMILATION
ENSEMBLE SENSITIVITY ANALYSIS
LOCALIZATION
OBSERVING SYSTEM
SAMPLING ERROR
topic CONVECTIVE-SCALE
COVARIANCE
DATA ASSIMILATION
ENSEMBLE SENSITIVITY ANALYSIS
LOCALIZATION
OBSERVING SYSTEM
SAMPLING ERROR
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv This study presents the first convective-scale 1,000-member ensemble simulation over central Europe, which provides a unique data set for various applications. A comparison with the operational regional 40-member ensemble of Deutscher Wetterdienst shows that the 1,000-member simulation exhibits realistic spread properties overall. Based on this, we discuss two potential applications. First, we quantify the sampling error of spatial covariances of smaller subsets compared with the 1,000-member simulation. Knowledge about sampling errors and their dependence on ensemble size is crucial for ensemble and hybrid data assimilation and for developing better approaches for localization in this context. Secondly, we present an approach for estimating the relative potential impact of different observable quantities using ensemble sensitivity analysis. This will provide the basis for consecutive studies developing future observation and data assimilation strategies. Sensitivity studies on the ensemble size indicate that about 200 ensemble members are required to estimate the potential impact of observable quantities with respect to precipitation forecasts.
Fil: Necker, Tobias. Ludwig Maximilians Universitat; Alemania. Universidad de Viena; Austria
Fil: Geiss, Stefan. Ludwig Maximilians Universitat; Alemania
Fil: Weissmann, Martin. Ludwig Maximilians Universitat; Alemania
Fil: Ruiz, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Fil: Miyoshi, Takemasa. RIKEN Center for Computational Science; Japón
Fil: Lien, Guo Yuan. RIKEN Center for Computational Science; Japón
description This study presents the first convective-scale 1,000-member ensemble simulation over central Europe, which provides a unique data set for various applications. A comparison with the operational regional 40-member ensemble of Deutscher Wetterdienst shows that the 1,000-member simulation exhibits realistic spread properties overall. Based on this, we discuss two potential applications. First, we quantify the sampling error of spatial covariances of smaller subsets compared with the 1,000-member simulation. Knowledge about sampling errors and their dependence on ensemble size is crucial for ensemble and hybrid data assimilation and for developing better approaches for localization in this context. Secondly, we present an approach for estimating the relative potential impact of different observable quantities using ensemble sensitivity analysis. This will provide the basis for consecutive studies developing future observation and data assimilation strategies. Sensitivity studies on the ensemble size indicate that about 200 ensemble members are required to estimate the potential impact of observable quantities with respect to precipitation forecasts.
publishDate 2020
dc.date.none.fl_str_mv 2020-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/143882
Necker, Tobias; Geiss, Stefan; Weissmann, Martin; Ruiz, Juan Jose; Miyoshi, Takemasa; et al.; A convective-scale 1,000-member ensemble simulation and potential applications; John Wiley & Sons Ltd; Quarterly Journal of the Royal Meteorological Society; 146; 728; 4-2020; 1423-1442
0035-9009
CONICET Digital
CONICET
url http://hdl.handle.net/11336/143882
identifier_str_mv Necker, Tobias; Geiss, Stefan; Weissmann, Martin; Ruiz, Juan Jose; Miyoshi, Takemasa; et al.; A convective-scale 1,000-member ensemble simulation and potential applications; John Wiley & Sons Ltd; Quarterly Journal of the Royal Meteorological Society; 146; 728; 4-2020; 1423-1442
0035-9009
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/qj.3744
info:eu-repo/semantics/altIdentifier/doi/10.1002/qj.3744
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons Ltd
publisher.none.fl_str_mv John Wiley & Sons Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842269898957389824
score 13.13397

Publicaciones similares